code: def test_batch_consistency(self):
      model = squim_subjective_base()
      model.eval()
  
      batch_size, num_frames = 3, 16000
      waveforms = torch.randn(batch_size, num_frames)
      reference = torch.randn(batch_size, num_frames)
  
      ref_scores = model(waveforms, reference)
      hyp_scores = []
      for i in range(batch_size):
          scores = model(waveforms[i : i + 1], reference[i : i + 1])
          hyp_scores.append(scores)
      hyp_scores = torch.tensor(hyp_scores)
      self.assertEqual(hyp_scores, ref_scores)
  
file_path: audio/test/torchaudio_unittest/models/squim/squim_test.py
imports: import torch
  from parameterized import parameterized
  from torchaudio.models import squim_objective_base, squim_subjective_base
  from torchaudio_unittest.common_utils import skipIfNoCuda, torch_script, TorchaudioTestCase
label_desc: Use image node_id 4 for calling the TestSquimSubjective obj's underlying member method code with example usage: obj.test_batch_consistency() without return types